Twin Dynamics is technology company offers smart building solutions to help making buildings healthier and greener. Twin Dynamics precisely tracks indoor air quality, ventilation, airflow, thermal distribution and aerosol transmission in real-time.
Twin Dynamics assesses the annual HVAC energy expenditures and carbon emissions and provides a solution to reduce the energy bills and emissions without comprising human comfort and air quality.
Twin Dynamics’ technology?
Learn MoreA Phd Research Scientist with expertise in Fluid Dynamics and Software Development. Noukhez is Digital Technologist, with many years of experience in design optimisation and advanced data analysis in the field of built environment, turbomachines and oil and gas. He has spent the past four years building Twin Dynamics into the digital transformation disruptor that it is today. From early beginnings, Noukhez has applied to IoT Tribe North Accelerator program and brought a new concept of Physics based Digital Twin. Noukhez is managing the entire business including lead generation, setting up deals and backend R&D work.
A PhD Research Scientist with expertise in Microfluidics and Machine Learning. Shrawasti is endorsed by the Tech Nation as an exceptional promise in Digital Technology Field. Shrawasti is an expert Data Scientist and used his skills and expertise in developing and enhancing Physics Based Digital Twin technology. He was majorly involved in developing Physics based Digital Twin algorithms. He has contributed towards Digital Twin adoption by integrating simulations with IoT data to capture realtime airflow behaviour and its dependent features including airborne disease transmission using Machine Learning algorithms.
A Phd Research Scientist with expertise in Fluid Dynamics and Software Development. Noukhez is Digital Technologist, with many years of experience in design optimisation and advanced data analysis in the field of built environment, turbomachines and oil and gas. He has spent the past four years building Twin Dynamics into the digital transformation disruptor that it is today. From early beginnings, Noukhez has applied to IoT Tribe North Accelerator program and brought a new concept of Physics based Digital Twin. Noukhez is managing the entire business including lead generation, setting up deals and backend R&D work.
A PhD Research Scientist with expertise in Microfluidics and Machine Learning. Shrawasti is endorsed by the Tech Nation as an exceptional promise in Digital Technology Field. Shrawasti is an expert Data Scientist and used his skills and expertise in developing and enhancing Physics Based Digital Twin technology. He was majorly involved in developing Physics based Digital Twin algorithms. He has contributed towards Digital Twin adoption by integrating simulations with IoT data to capture realtime airflow behaviour and its dependent features including airborne disease transmission using Machine Learning algorithms.
Founded HMU Design Engineering Limited Name changed to Twin Dynamics Limited in 2020.
2017Consultants to optimise egineering design using FEA and CFD
2017-2019Proposed idea of Digital Twinning and incubated by IoT Tribe North Accelerator Developed lab-based MVP on using Digital Twinning technology
2019Funded by Regional Funding and developed large scale prototype to see product viability and feasibility. Funded by Innovate UK to real-time monintor airborne disease transmission within large buildings.
2020Deployment of Twin Dynamics technology on actual building as our first commercial pilot on a large council building.
2021Founded HMU Design Engineering Limited Name changed to Twin Dynamics Limited in 2020.
2017Consultants to optimise egineering design using FEA and CFD
2017-2019Proposed idea of Digital Twinning and incubated by IoT Tribe North Accelerator Developed lab-based MVP on using Digital Twinning technology
2019Funded by Regional Funding and developed large scale prototype to see product viability and feasibility. Funded by Innovate UK to real-time monintor airborne disease transmission within large buildings.
2020Deployment of Twin Dynamics technology on actual building as our first commercial pilot on a large council building.
2021 - PresentThis project combined Computational Fluid Dynamics (CFD) with data-driven Machine Learning (ML) techniques to produce a system that can give detailed, intuitive information about one space in a large complex building.
This project adapted the developed MF-BM technology to predict near real-time airborne disease transmissions including COVID-19 and its predicted settlement locations and particles stranded in the air.
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